Focused On-demand Library for Ribonuclease H2 subunit B

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

We employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.







Alternative names:

Aicardi-Goutieres syndrome 2 protein; Deleted in lymphocytic leukemia 8; Ribonuclease HI subunit B

Alternative UPACC:

Q5TBB1; G3XAJ1; Q05DR2; Q6PK48; Q9HAF7


Ribonuclease H2 subunit B, also known as Aicardi-Goutieres syndrome 2 protein, plays a pivotal role in DNA replication. It functions as a non-catalytic subunit of RNase H2, an endonuclease that degrades RNA from RNA:DNA hybrids, facilitating the removal of RNA primers from Okazaki fragments during DNA replication and the excision of single ribonucleotides from DNA:RNA duplexes.

Therapeutic significance:

Linked to Aicardi-Goutieres syndrome 2, a severe neurological disorder, Ribonuclease H2 subunit B's dysfunction highlights its critical role in maintaining genomic integrity. Understanding its function could pave the way for novel therapeutic strategies targeting the syndrome and related genomic maintenance issues.

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